PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
January 22, 2026Metabolites0 citationsOpen Access

Distinct Metabolic Signatures Linked to High-Resolution Computed Tomography Radiographic Phenotypes in Stable and Progressive Fibrotic Lung Disease

View Full Paper
GNGirish B. NairFFFaizan FaizeeZSZachary D. Smith

Key Points

  • This study aims to identify metabolic signatures that correlate with high-resolution computed tomography scores in lung disease.
  • Cross-sectional study of 60 IPF/ILD patients with usual interstitial pneumonia pattern.
  • Participants underwent pulmonary function testing and HRCT imaging.
  • Peripheral blood was collected for metabolomic analysis using advanced spectroscopy techniques.
  • Correlations between metabolite levels and HRCT scores were analyzed using linear regression.
  • Stable IPF/ILD showed moderate negative correlations between key metabolites and HRCT scores.
  • Progressive disease exhibited weak positive correlations with specific metabolites.
  • Distinct phospholipid profiles were observed between stable and progressive disease groups.

Abstract

Background: This study aimed to identify distinct metabolic signatures associated with disease progression by integrating high-resolution computed tomography (HRCT) visual scoring with comprehensive metabolomic profiling. Materials and Methods: This single-center, cross-sectional study enrolled 60 idiopathic pulmonary fibrosis/interstitial lung disease (IPF/ILD) patients with usual interstitial pneumonia pattern. Participants underwent standardized pulmonary function testing, HRCT imaging, and peripheral blood collection for metabolomic analysis using one-dimensional hydrogen nuclear magnetic resonance spectroscopy and ultra-high-performance liquid chromatography coupled to tandem mass spectrometry. Linear regression analysis integrated radiographic scores with metabolomic profiles, adjusted for multiple covariates. Results: Stable IPF/ILD exhibited moderate negative correlations between the six most significant metabolites and HRCT scores (r = −0.27 to −0.51), along with a high abundance of specific phospholipids (triacylglycerol, monoacylglycerol, phosphatidylglycerol, phosphatidylethanolamine, diacylglycerol), sphingomyelin, ceramide, and acylcarnitine. In contrast, progressive disease showed weak positive correlations between the six most significant metabolites and HRCT scores (r = 0.19–0.26), and moderate negative correlation between specific triacylglycerol species and HRCT scores (r = −0.37–0.4). Furthermore, metabolomic analysis in individuals with progressive disease revealed both high and low abundances of specific phospholipid species (including high and low triacylglycerol species, as well as low levels of phosphatidylglycerol, phosphatidylethanolamine, phosphatidylcholine, phosphatidylserine, and phosphatidylinositol), along with high levels of certain sphingomyelin, ceramide, taurine, and purine bases, and low levels of xanthine and lactic acid observed. Conclusions: Integration of systematic HRCT semi-quantitative scoring with metabolomic profiling successfully differentiated stable from progressive IPF/ILD through distinct molecular-radiographic signatures.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Nair et al. (2026) studied this question.

synapsesocial.com/papers/6971bea8642b1836717e3581https://doi.org/10.3390/metabo16010082
Ask AI
Helpful
Bookmark
Share
View Full Paper